Optimizing Irrigation Strategies to Improve Water Use Efficiency of Cotton in Northwest China Using RZWQM2

Xiaoping Chen, Shaoyuan Feng, Zhiming Qi, Matthew W. Sima, Fanjiang Zeng, Lanhai Li, Haomiao Cheng and Hao Wu
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Xiaoping Chen: College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China
Shaoyuan Feng: College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China
Zhiming Qi: Department of Bioresource Engineering, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada
Matthew W. Sima: Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544, USA
Fanjiang Zeng: State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Lanhai Li: State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Haomiao Cheng: College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China
Hao Wu: College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou 225009, China

Agriculture, 2022, vol. 12, issue 3, 1-15

Abstract: Irrigated cotton ( Gossypium hirsutum L.) is produced mainly in Northwest China, where groundwater is heavily used. To alleviate water scarcity and increase regional economic benefits, a four-year (2016–2019) field experiment was conducted in Qira Oasis, Xingjiang Province, to evaluate irrigation water use efficiency (IWUE) in cotton production using the Root Zone Water Quality Model (RZWQM2), that was calibrated and validated using volumetric soil water content ( θ ), soil temperature ( T soil ° ) and plant transpiration ( T ), along with cotton growth and yield data collected from full and deficit irrigation experimental plots managed with a newly developed Decision Support System for Irrigation Scheduling (DSSIS). In the validation phase, RZWQM2 adequately simulated (S) topsoil θ and T soil ° , as well as cotton growth (average index of agreement (IOA) > 0.76). Relative root mean squared error (RRMSE) and percent bias (PBIAS) of cotton seed yield were 8% and 2.5%, respectively, during calibration, and 20% and −10.3% during validation. The cotton crop’s (M) T was well S (−18% < PBIAS < 14% and IOA > 0.95) for both full and deficit irrigation fields. The validated RZWQM2 model was subsequently run with seven irrigation scenarios with 850 to 350 mm water (Irr850, Irr750, Irr700, Irr650, Irr550, Irr450, and Irr350) and long-term (1990–2019) weather data to determine the best IWUE. Simulation results showed that the Irr650 treatment generated the greatest cotton seed yield (4.09 Mg ha −1 ) and net income (US $3165 ha −1 ), while the Irr550 treatment achieved the greatest IWUE (6.53 kg ha −1 mm −1 ) and net water production (0.94 $ m −3 ). These results provided farmers guidelines to adopt deficit irrigation strategies.

Keywords: RZWQM2; DSSIS; long-term irrigation; cotton seed yield; IWUE (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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